This invention relates to methods and systems for interactively developing at least one grid pattern such as a microarray pattern, as well as an array set of such patterns, and a computer-readable storage medium having a program for executing the methods.
An array pattern can be used to establish the expected locations of spots containing fluorescently labeled DNA samples on a suitable carrier such as a microscope slide or membrane. These are commonly known as microarrays or bio-chips. The locations are typically used in subsequent quantitative analysis using software and image processing algorithms.
An example of a process that is arranged in a grid pattern is the microarray. As previously mentioned, microarrays are created with fluorescently labeled DNA samples in a grid pattern consisting of rows 22 and columns 20 typically spread across a 1 by 3 inch glass microscope slide 24 as illustrated in FIG. 1. The rows 22 extend along the smaller dimension of the slide 24 and the columns 20 extend along the larger dimension of the rectangular slide 24. Each spot 26 in the grid pattern (or array) 28 represents a separate DNA probe and constitutes a separate experiment. A plurality of such grid pattern comprises an array set 30. Reference or xe2x80x9ctargetxe2x80x9d DNA (or RNA) is spotted onto the glass slide 24 and chemically bonded to the surface. Fluorescently labeled xe2x80x9cprobexe2x80x9d DNA (or RNA) is introduced and allowed to hybridize with the target DNA. Excess probe DNA that does not bind is removed from the surface of the slide in a subsequent washing process.
The purpose of the experiment is to measure the binding affinity between the probe and target DNA to determine the likeness of their molecular structures: complementary molecules have a much greater probability of binding than unrelated molecules. The probe DNA is labeled with fluorescent labels that emit light when excited by an external light source of the proper wavelength. The brightness of each sample on the slide 24 is a function of the fluor density in that sample. The fluor density is a function of the binding affinity or likeness of the probe molecule to the target molecule. Therefore, the brightness of each sample can be mapped to the degree of similarity between the probe DNA and the target DNA in that sample. On a typical microarray, up to tens of thousands of experiments can be performed simultaneously on the probe DNA, allowing for a detailed characterization of complex molecules.
Scanning laser fluorescence microscopes or microarray readers can be used to acquire digital images of the emitted light from a microarray as illustrated in FIG. 2. The digital images are comprised of several thousand to hundreds of millions of pixels that typically range in size from 5 to 50 microns. Each pixel in the image is typically represented by a 16 bit integer, allowing for 65,535 different grayscale values. The microarray reader sequentially acquires the pixels from the scanned microarray and writes them into an image file and stored on a computer hard drive.
As illustrated in FIG. 2, a confocal laser microarray scanner or microarray reader is commonly used to scan the microarray slide 24 to produce one image for each dye used by sequentially scanning the microarray with a laser of a proper wavelength for the particular dye. Each dye has a known excitation spectra as illustrated in FIG. 3 and a known emission spectra as illustrated in FIG. 4. The scanner includes a beam splitter 32 which reflects a laser beam 34 towards an objective lens 36 which, in turn, focuses the beam at the surface of slide 24 to cause fluorescence spherical emission. A portion of the emission travels back through the lens 36 and the beam splitter 32. After traveling through the beam splitter 32, the fluorescence beam is reflected by a mirror 38, travels through an emission filter 40, a focusing detector lens 42 and a central pinhole 44. After traveling through the central pinhole 44, the fluorescence beam is detected by a detector, all in a conventional fashion.
Analysis and Quantitation of the Microarray
Analysis of the fluor density at each spot location requires software that utilize image processing algorithms to locate all the spots and measure the brightness of the pixels in each spot. Typical image processing algorithms utilize one or more methods of thresholding the image to differentiate the background from a spot. Fixed and dynamic thresholding algorithms can be used depending upon the amount of variability of the background brightness across the image. Local area thresholding can also be used to minimize the negative affect of a variable background brightness.
Once a valid threshold is obtained, a temporary image of a lower number of grayscales, typically a binary image with two different grayscales, is created that clearly shows the background separated from the spots. The next step is typically to run a deformable grid algorithm to quantify the X and Y locations of each spot. The deformable grid algorithm is required to account for microarray manufacturing variations that commonly occur causing the spot positions to vary on an irregular basis. In order to measure the true brightness levels at each spot, the true spot position must be measured in real time since it can vary from array to array and from microarray to microarray.
Once the location of each spot is determined, additional image processing algorithms calculate the spot brightness of each spot. This is done with the original full resolution image. Typically, a sophisticated dynamic local area threshold technique is calculated using pixels within the local area 38 which belong to the background 40 and which belong to the spot 26 as illustrated in FIG. 3. Only the pixels that represent the spot 26 are used to calculate the brightness value for that spot 26. The final brightness value is typically calculated as the mean, mode, or sum of the pixels that represent the spot 26. The brightness value of the background 40 is also important to researchers, and is calculated in similar manner by the mean, mode, or sum of the pixels that represent the local background 40.
The location and analysis of spots and background process continues for each image obtained from the microarray sample by the microarray reader. The number can vary from one to four or more images per microarray and depends upon the number of differently labeled probe DNA samples used in the creation of the microarray.
The Need for a Regular Grid Pattern and How to Create One.
In order for a researcher to calculate the brightness of each spot and local background, also known as to xe2x80x9cquantitatexe2x80x9d the microarray, of a large microarray pattern, he/she must create a map or pattern of the microarray spot locations. To perform quantitation on a small number of spots, typically less than 100, a user can manually locate the spot. Manual location of spot patterns with more than 100 spots become cumbersome while larger arrays are impossible to quantitate in this manner. Also, with the progression of the microarray inspection towards automation, efficient and accurate methods to create the array patterns and quantitate the spots will be required. The microarray map is a template that is used by the software to efficiently search for the true locations of each spot in the pattern.
To fully describe a regular grid pattern, several parameters are requiredxe2x80x94the number of rows of spots, the number of columns of spots, the distance between each row, the distance between each column, and the average diameter of each spot. The most straightforward way of creating a regular grid pattern would be to manually enter appropriate values for each of the parameters above. This method, however, requires a-priori knowledge of the complete pattern of the array. This information is difficult to obtain because of the variation in microarray fabrication methods, typically either by hand and by automatic array spotting equipment, and the wide range of variability in each method.
The regular grid pattern is extended in common practice in the fabrication of microarrays to produce several copies of the same basic grid pattern across the microarray (manually though). These patterns are denoted as the array set 30 in FIG. 1. The additional parameters required to specify the array set are the number of arrays in each row, the number of arrays in each column, the distance between the upper left spot in each array along a row, and the distance between the upper left spot in each array along a column.
A company named BioDiscovery has a commercially available quantitation software package named ImaGene(trademark). This software package requires the researcher to manually type in the number of rows and columns of spots for the array, and point to and click on the four corner spots 42 of the array 44, to be able to calculate the row and column spacing values as shown in FIG. 4. Additionally, to create array sets, the software requires the researcher to enter the number of arrays in the set 46 along both the row and column direction and point to and click on the upper left spot 48 in each of the four corner arrays. The array spacing along the row and column are calculated by the software.
U.S. Pat. No. 5,680,514 discloses a multiple elastic feature net and a method for target deghosting and tracking.
An object of the present invention is to provide a method and system for interactively developing at least one grid pattern, such as a microarray pattern, as well as an array set of such patterns, and a computer-readable storage medium having a program for executing the method wherein a user need not know the number of rows or columns before creating the array pattern.
Another object of the present invention is to provide a method and system for interactively developing at least one grid pattern, such as a microarray pattern, as well as an array set of such patterns, and a computer-readable storage medium having a program for executing the method wherein a user can create an accurate array pattern without any knowledge of the physical dimensions of the microarray pattern.
Yet another object of the present invention is to provide a method and system for interactively developing at least one grid pattern, such as a microarray pattern, as well as an array set of such patterns, and a computer-readable storage medium having a program for executing the method wherein the software automatically records the required dimensions without manual entry by the user.
In carrying out the above objects and other objects of the present invention, a method for interactively developing at least one grid pattern from at least one digital image of rows and columns of spots is provided. The method includes displaying the rows and columns of spots including a corner spot located in one of the rows and columns. The method also includes receiving a first set of commands from a user to select an approximate location of the corner spot to obtain pattern origin data. The method then includes processing the at least one digital image and the pattern origin data to obtain the at least one grid pattern. The at least one grid pattern includes rows and columns of grid elements and wherein the step of processing includes the step of calculating the number of rows and columns of grid elements, average spacing between adjacent rows and average spacing between adjacent columns of grid elements.
The method may also include receiving a second set of commands from a user to select at least one edge of one of the spots to obtain spot dimension data. The spot dimension data is then processed with the pattern origin data and the at least one digital image to obtain the at least one grid pattern.
The method may include receiving a third set of commands from a user to select at least one row spot in the same row as the corner spot to obtain row data. The at least one row spot includes a spot furthest away from the corner spot. The row data is then processed with the pattern origin data and the at least one digital image to obtain the at least one grid pattern.
The method may further include receiving a fourth set of commands from a user to select at least one spot in the same column as the corner spot to obtain column data. The at least one column spot includes a spot furthest away from the corner spot. The column data is then processed with the pattern origin data and the at least one digital image to obtain the at least one grid pattern.
Preferably the step of receiving the second set of commands from the user selects two opposite edges of the one of the spots and wherein the spot dimension data is spot diameter data.
Also, preferably, the step of receiving the third set of commands selects two row spots in the same row as the corner spot to obtain the row data.
The step of receiving the fourth set of commands selects two column spots in the same column as the corner spot to obtain the column data.
The at least one grid pattern may be a microarray pattern.
The method may be extended to interactively develop a regular pattern of grid patterns including the at least one grid pattern from the at least one digital image. The regular pattern of grid patterns defines an array set. The rows and columns of spots define rows and columns of arrays. The method further includes receiving a fifth set of commands from a user to select at least one row corner spot in the row of arrays corresponding to the corner spot of the at least one grid pattern to obtain row array data. The at least one row corner spot is in an array furthest from the at least one grid pattern in the same row of arrays as the at least one grid pattern. The method further includes receiving a sixth set of commands from a user to select at least one column corner spot in the column of arrays corresponding to the corner spot of the at least one grid pattern to obtain column array data. The at least one column corner spot is in an array furthest from the at least one grid pattern in the same column of arrays. The step of processing also processes the row array data and the column array data with the spot dimension data, the pattern origin data and the row and column data to obtain the regular pattern of grid patterns.
Each of the grid patterns may be a microarray pattern.
Preferably, the step of receiving the fifth set of commands selects two row corner spots in the same row of arrays as the at least one grid pattern to obtain the row array data.
The step of receiving the sixth set of commands preferably selects two column corner spots in the same column of arrays as the at least one grid pattern to obtain the column array data.
The method may further include displaying a value representing distance between columns or rows of spots.
Preferably, the step of processing includes the step of processing the spot dimension data and the pattern origin data to obtain a bounded area of image data which encompasses either the row or the column of spots including the corner spot. The step of processing further includes the step of performing a profile projection of the image data in the bounded area to obtain profile projection data. The step of processing also includes the step of calculating a spot model projection based on the spot dimension data. The step of processing then includes the steps of utilizing the spot model projection as a correlation model and comparing the correlation model with sections corresponding to each spot along the profile projection in the bounded area. Still further, the step of processing includes the step of calculating a correlation coefficient between the correlation model and each similar feature within the profile projection data to identify features representing spots in the bounded area.
Still further, the step of processing includes the step of calculating a best fitted pitch value using an outlier removal based line fitting algorithm.
The step of processing also includes the step of calculating distance between adjacent rows of arrays and distance between adjacent columns of arrays.
Further, in carrying out the above objects and other objects of the present invention, a system for carrying out the above method steps and a computer-readable storage medium having a program for executing the method are provided.
The above objects and other objects, features, and advantages of the present invention are readily apparent from the following detailed description of the best mode for carrying out the invention when taken in connection with the accompanying drawings.